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» Relevance Evaluation of Search Engines' Query Results
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ECAI
2000
Springer
15 years 5 months ago
Similarity-based Approach to Relevance Learning
In several information retrieval (IR) systems there is a possibility for user feedback. Many machine learning methods have been proposed that learn from the feedback information in...
Rickard Cöster, Lars Asker
103
Voted
EDBT
2006
ACM
169views Database» more  EDBT 2006»
16 years 29 days ago
Feedback-Driven Structural Query Expansion for Ranked Retrieval of XML Data
Relevance Feedback is an important way to enhance retrieval quality by integrating relevance information provided by a user. In XML retrieval, feedback engines usually generate an ...
Ralf Schenkel, Martin Theobald
SIGIR
2008
ACM
15 years 22 days ago
Enhancing web search by promoting multiple search engine use
Any given Web search engine may provide higher quality results than others for certain queries. Therefore, it is in users' best interest to utilize multiple search engines. I...
Ryen W. White, Matthew Richardson, Mikhail Bilenko...
86
Voted
IJCAI
2007
15 years 2 months ago
Opinion Sentence Search Engine on Open-Domain Blog
We have introduced a search engine that can extract opinion sentences relevant to an open-domain query from Japanese blog pages. The engine identifies opinions based not only on p...
Osamu Furuse, Nobuaki Hiroshima, Setsuo Yamada, Ry...
KDD
2002
ACM
169views Data Mining» more  KDD 2002»
16 years 1 months ago
Optimizing search engines using clickthrough data
This paper presents an approach to automatically optimizing the retrieval quality of search engines using clickthrough data. Intuitively, a good information retrieval system shoul...
Thorsten Joachims